agent-reliability

Enforces verification, self-correction, and scope discipline rules for AI coding agents.

3|2|Updated Aug 24, 2026
One-click install
npx skills add https://github.com/hero-engine/hero --skill agent-reliability-hero-engine
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-reliability
Source: https://github.com/hero-engine/hero/tree/main/core/skills/agent-reliability
Command: npx skills add https://github.com/hero-engine/hero --skill agent-reliability-hero-engine

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI coding agents frequently hallucinate file paths and APIs, claim work is done without running tests, drift beyond the requested scope, or stop mid-task and ask for permission to continue. This Skill provides behavioral guardrails that prevent these failure modes during code changes. ## Core Features & Use Cases - Verification rules: Requires reading files before editing, running tests or linters after changes, and reviewing diffs before declaring completion. - Hallucination prevention: Mandates grounding proposals in inspected source code, marking claims as read or assumed, and stating uncertainty explicitly. - Scope and persistence discipline: Enforces one logical change at a time, the Two-Reading Rule for ambiguous requirements, and continuing multi-step tasks until a true blocker is hit. - Use Case: An engineer agent implementing a multi-phase spec uses these rules to verify each change with the test suite, avoid silently reclassifying acceptance criteria, and produce a Completion Ledger accounting for every item. ## Quick Start Load the agent-reliability skill so the agent verifies every code change with tests and stays within the requested scope.

Frequently Asked Questions about agent-reliability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I stop an AI coding agent from hallucinating file paths and APIs?▼

Require the agent to read directories before assuming files exist and to inspect source or documentation before using an API. The skill's grounding rule makes the agent mark each load-bearing claim as read or assumed before proposing a fix.

How to make an AI agent verify code changes before claiming completion?▼

Instruct the agent to run the project's test suite, linter, or type checker after every change and to review the diff for typos and missing imports. If no test command is known, the agent must say so explicitly rather than claim success.

What is the Two-Reading Rule for ambiguous requirements?▼

When a requirement has two plausible readings, the agent must name both and pick the more thorough one, or pause and ask. It may not silently choose the easier interpretation, and verbs like "implement" default to making the feature actually work.

Why does an AI agent stop mid-task and ask to continue?▼

Unilateral mid-task stops are treated as a failure mode. The agent must continue until the work is complete, a true blocker occurs such as a missing credential or unrecoverable tool error, or the user explicitly interrupts.

When should an agent stop an investigation without a full answer?▼

Investigation tasks can hit genuine dead ends requiring production data or stakeholder input. A report describing findings, where the trail goes cold, and what is needed next is a valid complete output, while looping over the same searches is not.